D3.js vs NumPy vs Pandas

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D3.js

1.6K
1.4K
+ 1
616
NumPy

810
583
+ 1
6
Pandas

1.1K
919
+ 1
19
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Pros of D3.js
Pros of NumPy
Pros of Pandas
  • 182
    Beautiful visualizations
  • 93
    Svg
  • 90
    Data-driven
  • 79
    Large set of examples
  • 60
    Data-driven documents
  • 22
    Visualization components
  • 20
    Transitions
  • 18
    Dynamic properties
  • 14
    Plugins
  • 11
    Transformation
  • 5
    Makes data interactive
  • 4
    Enter and Exit
  • 4
    Components
  • 3
    Backed by the new york times
  • 2
    Open Source
  • 2
    Exhaustive
  • 2
    Easy and beautiful
  • 1
    Awesome Community Support
  • 1
    Angular 4
  • 1
    Simple elegance
  • 1
    Kris
  • 1
    Templates, force template
  • 6
    Great for data analysis
  • 18
    Easy data frame management
  • 1
    Extensive file format compatibility

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Cons of D3.js
Cons of NumPy
Cons of Pandas
  • 5
    Beginners cant understand at all
  • 4
    Complex syntax
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      What is D3.js?

      It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.

      What is NumPy?

      Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

      What is Pandas?

      Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

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      Jobs that mention D3.js, NumPy, and Pandas as a desired skillset
      What companies use D3.js?
      What companies use NumPy?
      What companies use Pandas?

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      What tools integrate with D3.js?
      What tools integrate with NumPy?
      What tools integrate with Pandas?

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      Blog Posts

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      What are some alternatives to D3.js, NumPy, and Pandas?
      three.js
      It is a cross-browser JavaScript library and Application Programming Interface used to create and display animated 3D computer graphics in a web browser.
      Plotly.js
      It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.
      Highcharts
      Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.
      Python
      Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
      Tableau
      Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
      See all alternatives
      Reviews of D3.js, NumPy, and Pandas
      Cofounder
      Review of
      D3.js

      There is so much to like about D3js. It's Javascript, SVG, interactive, it's flexible, fairly well documented...definitely one of the most powerful tools in my webdev toolbox. On top of all that, I occasionally use D3 to produce my version of art.

      How developers use D3.js, NumPy, and Pandas
      datapile uses
      D3.js

      D3.js is an amazing library for doing visualizations, charts/graphs, etc. We are experimenting with it for metric visualizations, marketing graphs/charts, and basically anywhere we could use this amazing library.

      Software Antelope uses
      D3.js

      Creating online data visualizations to illustrate your potential or interact in new ways with your users. Including transistions, animations and graphs.

      Kent Steiner uses
      D3.js

      Charts, charts, charts. Data visualizations are a great way to communicate information to people who need to know it, quickly and concisely.

      Vital Labs, Inc. uses
      NumPy

      We utilize NumPy, SciPy, Pandas, and iPython Notebooks to power our analysis and analytics tools.

      MOKA Analytics uses
      D3.js

      We use D3 for creating custom charts that aren't available in off-the-shelf libraries

      Clarabridge Engage uses
      D3.js

      Several of the visualisations in our Insights pages use D3.js as their engine.

      Morris Clay uses
      Pandas

      Data wrangling, analysis and pre-processing

      GadgetSteve uses
      Pandas

      Great data manipulation tool

      GadgetSteve uses
      NumPy

      Fast Numeric Processing

      Nough You uses
      NumPy

      Fast array operations.

      BobStein uses
      NumPy

      big data analysis

      Andrea Catalucci uses
      NumPy

      Number crunching